Automate Contract Management with Python: Extract, Clean, and Move Files

1. Introduction

A fan asked for a Python automation solution to process a contract spreadsheet: extract contract names with regex, remove characters like "第" and "批", and then move matching contract files to a new folder.

2. Implementation

The first step reads the Excel file, extracts the contract name, converts Chinese numerals, and cleans unwanted characters.

import pandas as pd
import re
from chinesenumber import NumberParser
numberparse = NumberParser()

df = pd.read_excel("test.xlsx")
# Extract contract name inside parentheses
df["合同名称"] = df["合同名称"].str.extract(r"（.*?）.*?（(.*?)）")
# Convert Chinese numbers to Arabic
df["合同名称_new1"] = df["合同名称"].apply(lambda x: numberparse.numberify(x))
# Remove characters "第" and "批"
df['合同名称_new2'] = df['合同名称_new1'].str.replace(r'(第|批)', '', regex=True)
print(df["合同名称_new2"])
df.to_excel('test1.xlsx')

The cleaned contract names are displayed in the following image:

The second step walks the source directory, finds files whose names contain the cleaned contract name, and copies them to the target folder.

import pandas as pd
import re
import os
import shutil

def copy_file(file_name):
    for root, dirs, files in os.walk(source_path):
        for file in files:
            if file_name in file:
                print(file)
                shutil.copyfile(root + '\\' + file, target_path + '\\' + file)
                print(root + '\\' + file + ' copied -> ' + target_path)

if __name__ == '__main__':
    source_path = r'xxx\source_path'
    target_path = r'C:\Users\Desktop\res'
    df = pd.read_excel("test1.xlsx")
    df["合同名称_new2"] = df["合同名称_new2"].apply(lambda x: copy_file(x))
    print("over!")

After execution, the files are successfully moved as shown in the image below.

3. Summary

The tutorial demonstrates a complete Python workflow for extracting, cleaning, and relocating contract files, providing reusable code snippets for similar data‑processing automation tasks.